Color constancy is often modeled on the assumption that color appearance in natural scenes is a function of the visual system's estimates of surface reflectance. Some stimuli, however, do not look like illuminated surfaces. Instead, they appear to be self-luminous. We hypothesized that the appearance of luminosity occurs when the visual system estimates a reflectance spectrum that is outside th...

Many recent computational models of surface color perception presuppose information about illumination in scenes. The models differ primarily in the physical process each makes use of as a cue to the illuminant. We evaluated whether the human visual system makes use of any of three of the following candidate illuminant cues: (1) specular highlight, (2) full surface specularity [Lee, H. C. (1986...

An alternative to the von Kries scaling underlying the chromatic adaptation transforms found in colour appearance models such as CIECAM02 is suggested for predicting what the colour signal (e.g., XYZ) reflected from a surface under a first illuminant is likely to become when lit instead by a second illuminant. The proposed method, G2M, employs metameric Gaussian-like functions to model the illu...

This work briefly describes a model for illuminant estimation based on combination of candidate illuminant cues. Many of the research issues concerning cue combination in depth and shape perception translate well to the study of surface color perception. I describe and illustrate a particular experimental approach (perturbation analysis) employed in the study of depth and shape that is useful i...

The human visual system is able to accurately determine the color of objects irrespective of the spectral power distribution used to illuminate the scene. This ability to compute color constant descriptors is called color constancy. Many different algorithms have been proposed to solve the problem of color constancy. Usually, some assumptions have to be made in order to solve this problem. Algo...

Knowledge of the full illuminant spectral power distribution is useful for many imaging applications. In most applications, however, accurate estimation is impossible because very few color measurements are made. In many of these cases, however, a great deal is known about the potential set of illuminants. In these cases, classification of scene illumination, rather than estimation of the full ...

Estimating the color of the illuminant under which an image of a scene was captured is a central part of solving the color constancy problem: that is, of deriving an illuminant independent representation of the re ectances in a scene. In this paper we develop a general correlation framework for solving the illuminant estimation problem. Within this framework estimation is posed as a correlation...

I report the results of a set of experiments designed to study whether the visual system's adjustments to illuminant changes vary with the surface collection in a scene. Simulations of flat matte surfaces rendered under diffuse illumination were presented on a CRT monitor. Under several surface collections subjects set asymmetric color matches between a standard surface and a test surface that ...

Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibil...